Abstract 1169: Genomic evolution of pancreatic cancer at single-cell resolution

Abstract As the breadth of genomic sequencing datasets increases, we can engage more directly with the evolutionary principles governing cancer progression. But as clonal evolution happens at the single-cell level, one must rely on strong assumptions when making conclusions with bulk-sequencing results, which fails in capturing clonal heterogeneity to its fullest. Herein we have developed and optimized a high-throughput, high-depth targeted single-nucleus DNA-seq (snDNA-seq) technique (doi.org/10.1101/2022.03.06.483206) for archival primary solid tumor samples. We focused on pancreatic ductal adenocarcinoma (PDAC), well known as one of the most lethal cancers, and sequenced over 200,000 single nuclei from 80 archival primary samples of 25 PDAC patients. The samples included both early- and late-stage diagnoses and multiregional sampling from primary tumors and metastasis to capture clonal heterogeneity on both temporal and spatial scales. With significant increase in sensitivity than bulk (down to mutations in 0.1% cells), we discovered thousands of novel mutations per sample on our 120,000 base-pair-long panel regions, suggesting a mutation rate higher than previously estimated. A small fraction of these mutations is in 1-10% single cells and are enriched in early-stage samples. They form mutually exclusive clones which functionally target key pathways including TGF-β, homologous recombination, suggesting subclonal evolution under positive selection at the early stage of cancer. Most novel mutations are in <1% single cells sampled and enabled us to measure convergent evolution and positive/negative selection within each tumor. We next revisited PDAC’s genomic evolution model established by bulk studies. It posits that PDAC often arises when KRAS hotspot mutation-bearing precursors acquire TP53 and/or CDKN2A inactivation through stepwise and punctuated evolution. While it assumes that TGF-β inactivating mutations are present in all cancer cells (clonal), we found that they are targeted in a highly subclonal manner; moreover, short mutations and focal copy number variations occur in a stepwise manner over time leading to the most “fit” genotype. In many PDACs whose bulk results show no alteration to the TGF-β pathway, snDNA-seq shows focal deletions that are likely below bulk’s sensitivity. Ongoing studies have begun to extend these analyses to longitudinal samples to study treatment response; normal pancreas tissues to study pancreas cells’ clonal evolution in aging and chronic disease conditions; blood samples to investigate circulating tumor cells in PDAC patients. Computational pipelines and analysis tools are being built as platform for more in-depth analyses. Overall, the high-throughput snDNA-seq technique brings genomic study of PDAC to a much higher resolution and holds the promise to not only inform precision medicine but also shed light on many fundamental questions on cancer evolution. Citation Format: Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Benjamin J. Raphael, Christine A. Iacobuzio-Donahue. Genomic evolution of pancreatic cancer at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1169.